Analysis on the Development of the Pet Industry Based on Multi-Step Combined Model

Authors

  • Junpeng Yuan
  • Jiaqi Zhang
  • Yuexin Sun
  • Lin Zhang
  • Dang Gan

DOI:

https://doi.org/10.54097/tnzzh231

Keywords:

Cubic spline interpolation, Multiple linear regression, Factor analysis, Multi-step difference equation, Production and export model.

Abstract

The multi-step combined model integrates multiple sub-models in sequential steps based on the internal correlations among factors. This paper formulates sub-problems for relevant issues, establishes corresponding sub-models, and ultimately solves them through integration. Through multiple linear regression, equations were derived for each outcome variables. A multi-order differential regression equation was applied to historical total scores. Combining predictions from direct, first-order difference, second-order difference regression, a weighted average (0.6,0.3,0.1) was calculated. The global pet food demand scores were predicted to be 33445.32, 33445.32, and 34157.15, with annual growth rates of 0.757%, 0.941%, and 1.176%.

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Published

09-10-2025

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Articles